Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.12.16.628734

Individual Alpha Frequency Predicts the Sensitivity of Time Perception

Abstract

A growing body of research links individual differences in the alpha-band frequency to temporal aspects of perception. However, whether the human alpha rhythm is a correlate of time perception itself has remained controversial. This study combined EEG with multiple duration perception tasks to evaluate whether individual alpha frequency (IAF) is associated with sensitivity or bias in judging visual durations across a range of peri-second durations (spanning 100-1200ms). In a temporal estimation task, participants (n = 55; 38 female, 13 male, 4 non-binary) reported the duration of a single stimulus between 300-1200ms. In a temporal discrimination task, participants reported which of two stimuli was longer: a standard (100, 600, or 1200ms) or comparison (50-150% of the standard). Stimuli also varied in whether their luminance was static or dynamically varying over time. We found that IAF was significantly related to the variance of duration estimates, a precision measure, but not average duration estimates, a bias measure. Further supporting this relationship, psychometric function slopes obtained from the independent duration discrimination tasks were positively correlated with IAF, particularly for the static stimulus conditions. These individual differences effects held when controlling for participant age. We also explored trial-level variability in alpha frequency and found it was predictive of shifts in the point of subjective equality (PSE) during discrimination of very short (100ms). Taken together, these results suggest that IAF plays a role in shaping individual differences in the sensitivity of time perception and that spontaneous variations around ones IAF can lead to a bias in temporal representations. Significance StatementBrain waves in the 8-13 Hz range, known as alpha waves, have long been hypothesized to modulate our perception of time, yet the evidence remains unclear. This study investigates the relationship between an individuals alpha frequency (IAF) and temporal sensitivity using a wide range of time perception tasks and stimulus durations to address gaps in the literature. We demonstrate that IAF is significantly associated with the precision of duration estimates and sensitivity in duration discrimination, particularly for static unchanging stimuli. These findings provide novel evidence that IAF shapes individual differences in time perception, emphasizing its role as a neural marker of temporal sensitivity.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Morrow, A., Wilson, M., Geller-Montague, M., Soldano, S., Hajidamji, S., Samaha, J.. 2024-12-17. Individual Alpha Frequency Predicts the Sensitivity of Time Perception. https://doi.org/10.1101/2024.12.16.628734

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗